Instructions to use NaukNauk/minimax-h3-turbo-fl2va-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
MiniMax-H3 FL2VA + Larry v4 Turbo (merged transformer)
This repository contains the premerged FL2VA transformer only for native
MiniMax-H3 first-frame, last-frame, and first+last-frame video-and-audio generation.
It must be assembled with the non-transformer components from the pinned
MiniMaxAI/MiniMax-H3 FL2VA partition before serving.
Pinned provenance
- Base:
MiniMaxAI/MiniMax-H3@42ed227ee7df40d41602854ae760620d6eb651fe, partitionFL2VA - LoRA:
larryvrh/MiniMax-H3-Turbo-Lora@43a74557ac3f6539db8e0f2a959d03feb7a81480 - File:
minimax_h3_turbo_v4_step600_ema.safetensors - LoRA SHA-256:
5f3a626cd72c93a8b9318d6760c510bc5092d2ab13aaba1f932c5bab07a416d3 - Merge scale:
1.0 - Merged targets:
259 - Arithmetic: base dtype output with FP32 chunked
W + B @ Aaccumulation
The Larry v4 model card recommends 4–8 denoiser evaluations. With SGLang's H3
scheduler contract, num_inference_steps: 9 produces 8 denoiser evaluations.
SGLang request mode
Serve the assembled model with --model-variant fl2va. A classic image-to-video
request supplies one image condition with role: "keyframe" and frame_index: 0.
Use -1 for a last-frame condition, or ordered [0, -1] conditions for both.
This derivative remains subject to the MiniMax-H3 community license linked above.
The source LoRA is Apache-2.0 licensed. Repository ID: NaukNauk/minimax-h3-turbo-fl2va-merged.
Model tree for NaukNauk/minimax-h3-turbo-fl2va-merged
Base model
MiniMaxAI/MiniMax-H3